2. PROJECT SUMMARY (See instructions): Melanoma has the fastest growing incidence among all cancers in the United States; researchers estimate there were over 62,000 new melanoma cases in 2008. Most patients with melanoma present with early stage disease and are cured with surgery alone. However, despite their overall good outcome, more than 15% of melanoma patients will suffer a recurrence. Standard clinical features (tumor thickness, ulceration, sentinel lymph node status) cannot completely predict which patients will recur. For those who do recur, current therapies are effective in only a minority. Thus, identifying more effective biologic markers to select high-risk patients for adjuvant therapies, identify those who will respond to treatment, elucidate mechanisms of recurrence, and suggest novel therapies is a necessity. One important way to identify relevant biologic markers is to examine the relationship of human genetic variation (genetic polymorphisms) to disease recurrence and progression, and an important potential mechanism regulating melanoma recurrence and progression is variation in the immune and inflammatory response to melanoma. Our recent investigations have identified specific polymorphisms in human leukocyte antigen (HLA) class II and transforming growth factor-iSl (TGF-i81) genes as markers of prognosis in early-stage melanoma patients. HLA class II polymorphisms can regulate melanoma immune responses by differential binding of peptide antigens, whereas TGF-|31 polymorphisms can regulate tumor growth and metastasis by differential expression of TGF-jSI and immunomodulation. We hypothesize that genetic polymorphisms in these and other immune and inflammatory genes influence host response to melanoma and thereby melanoma progression. We propose a coordinated investigation of our most promising and mechanistically related polymorphisms in a large cohort of patients with melanoma (Aim 1) together with a genome-wide analysis to identify candidate loci most strongly linked with melanoma progression (Aim 2). We will use this information to develop an integrated and iterative risk model of melanoma progression incorporating clinical, histopathologic, serologic, and genetic information from more than 2000 patients with melanoma (Aim 3).